"""Read and change a lane's live pool, over the broker. Milestone 422 step 2. The half of the milestone that does something. ## No docker socket is involved, and that is the point Milestone 365 put "acting on the state" out of scope because restarting a dead worker needs a docker socket the web container deliberately does not have. That is true of RESTARTING a container. It is not true of changing how much work a RUNNING worker does: celery's remote control sends a message over the broker and the worker resizes its own pool. Same Redis the app already uses, no new privilege, no new surface. pool_grow / pool_shrink how many slots a lane runs add_consumer / cancel_consumer whether it consumes its queues at all The operator ruled the socket out independently (2026-09-22: *"this feature is a very invasive idea in my mind and I'd like to avoid it"*), and nothing here raises the question. ## The setting is PER PROCESS, not per lane total `pool_grow(n, destination=[...])` adds n slots to EACH destination it names. While the stack still runs several containers per lane — the operator's production `worker` is `replicas: 2` — a single delta applied to a lane's total would be wrong for every replica. So `slots` means what `CELERY_CONCURRENCY` means: the pool size of one process. The reconcile below drives EACH replica to that number independently, computing its own delta from that replica's current pool, so replicas that have drifted apart (one restarted, one was grown) converge rather than being moved in lockstep from a shared baseline. After step 5 there is one process per lane and the distinction disappears. It matters now, and getting it wrong now would be invisible — the totals would simply be double what the UI claimed. ## Why reserved() is read alongside the queue depth Celery PREFETCHES: a worker pulls more messages than it can run and holds them in memory. Those have already left the Redis list, so `LLEN` — which is what `/api/system/activity/queues` reports — can read 0 while thirty tasks are waiting inside a worker. Any judgement about backlog that uses only LLEN under-reports, which matters for the UI and is disqualifying for step 7's autoscaler. """ from __future__ import annotations import asyncio import logging from dataclasses import dataclass, field from datetime import UTC, datetime from sqlalchemy import func, select from sqlalchemy.ext.asyncio import AsyncSession from ..models import TaskRun, WorkerLane from .worker_lanes import LANES, LANES_BY_QUEUE_KEY, Lane, derived_ceiling log = logging.getLogger(__name__) # celery control is a broker round trip on a request path, so it gets a # deadline (rule 156) — the same reasoning and the same budget as # service_roster's inspect. A broker that stopped answering must make this # report "not present", which is true, rather than hang the page. CONTROL_TIMEOUT_SECONDS = 2.0 @dataclass class LaneLiveState: """What `celery inspect` says about one lane right now. `present=False` is NOT "zero slots" — it is "nothing answered". A lane whose worker is restarting, or whose broker is unreachable, must read as unknown rather than as stopped: an unswept absence is not a verdict (snippet #3969). The reconcile in step 3 skips an absent lane rather than correcting it, which is only safe because this distinction is kept. """ present: bool = False replicas: int = 0 active: int = 0 reserved: int = 0 hostnames: list[str] = field(default_factory=list) # The queues this lane is actually consuming right now, across replicas. # Distinct from the lane's CONFIGURED queues: `cancel_consumer` stops a # worker consuming one without changing what it was started with, which # is how `enabled=false` is implemented. The reconcile needs this to tell # "already disabled" from "needs disabling" — without it, it would re-send # add_consumer for every queue on every tick forever (lesson #4183). consuming: set[str] = field(default_factory=set) # Pool size PER HOSTNAME, not aggregated. The resize below computes each # replica's own delta from its own current pool, so replicas that have # drifted apart converge instead of being moved in lockstep from a shared # baseline — which is what an aggregate here would silently reintroduce. pools: dict[str, int] = field(default_factory=dict) @property def pool(self) -> int | None: """One number for the UI. `max` rather than a sum: `slots` means the pool size of ONE process (see the module docstring), so the largest replica is the honest answer to "what is this lane set to". None when no replica reported — unknown, never zero.""" return max(self.pools.values()) if self.pools else None @property def capacity(self) -> int: """Total slots across replicas — how many tasks this lane can run at once. Distinct from `pool`, and the two must not be confused: `pool` is the DIAL (one process's size, what grow/shrink move), `capacity` is the CAPABILITY. Asking "is this lane saturated" compares `active`, which is summed across replicas, against this — against `pool` it would call two half-busy replicas of 4 saturated at 4 active.""" return sum(self.pools.values()) def _lane_for_queues(queues: tuple[str, ...]) -> Lane | None: return LANES_BY_QUEUE_KEY.get(tuple(sorted(queues))) def inspect_lanes_sync() -> dict[str, LaneLiveState]: """Live state per lane name. Sync — callers wrap in asyncio.to_thread. Never raises. Every lane is present in the result; ones nothing answered for carry `present=False`, so a caller cannot accidentally read a missing lane as an empty one by iterating only what came back. """ out = {lane.name: LaneLiveState() for lane in LANES} try: from ..celery_app import celery as celery_app insp = celery_app.control.inspect(timeout=CONTROL_TIMEOUT_SECONDS) active_queues = insp.active_queues() or {} stats = insp.stats() or {} active = insp.active() or {} reserved = insp.reserved() or {} except Exception: log.warning("worker_control: celery inspect failed", exc_info=True) return out for hostname, queues in active_queues.items(): lane = _lane_for_queues(tuple(q["name"] for q in queues)) if lane is None: # A deployment slicing CELERY_QUEUES differently. Reported by the # roster under its raw queue list; it simply has no lane row to # control, which is honest rather than an error. continue state = out[lane.name] state.present = True state.replicas += 1 state.hostnames.append(hostname) state.active += len(active.get(hostname, [])) state.reserved += len(reserved.get(hostname, [])) state.consuming.update(q["name"] for q in queues) # `pool.max-concurrency` is the number pool_grow/pool_shrink move and # the number the UI shows. Absent on a worker whose stats did not # answer, which leaves pool=None — unknown, not zero. pool = (stats.get(hostname) or {}).get("pool", {}).get("max-concurrency") if isinstance(pool, int): state.pools[hostname] = pool for state in out.values(): state.hostnames.sort() return out def set_lane_slots_sync( lane: Lane, target: int, live: LaneLiveState | None = None, ) -> tuple[bool, str | None]: """Drive every replica of `lane` to `target` slots. Returns (applied, err). Per-replica deltas rather than one shared delta: see the module docstring. A replica already at the target is issued nothing at all, which is what makes step 3's periodic reconcile converge instead of re-sending a grow of zero forever (lesson #4183 — an enforcer without a reachable fixed point re-does its own work every tick). `applied=False` is not a failure of the SETTING. The caller has already stored the value; this says only that the live push did not land, and the reconcile will carry it when the lane answers again. """ try: from ..celery_app import celery as celery_app if live is None: live = inspect_lanes_sync()[lane.name] if not live.present: return False, "lane is not running" if not live.pools: return False, "worker did not report its pool size" control = celery_app.control unreported = [h for h in live.hostnames if h not in live.pools] for hostname, current in live.pools.items(): delta = target - current if delta > 0: control.pool_grow(delta, destination=[hostname]) elif delta < 0: control.pool_shrink(-delta, destination=[hostname]) if unreported: # Resized what could be resized, and said which could not. Silence # here would leave a replica running at a size the UI claims it is # not, with nothing anywhere recording the gap. return False, f"no pool size reported by {', '.join(sorted(unreported))}" return True, None except Exception as exc: # noqa: BLE001 — reported, never raised at a caller log.warning("worker_control: could not resize %s", lane.name, exc_info=True) return False, str(exc) def set_lane_enabled_sync( lane: Lane, enabled: bool, live: LaneLiveState | None = None, ) -> tuple[bool, str | None]: """Start or stop `lane` consuming its queues, without killing the process. `cancel_consumer` rather than a shutdown: a stopped consumer keeps its worker alive and answering `inspect`, so a disabled lane stays visible and can be turned back on. A killed worker would read as absent, which is the same signal as a crash — and the whole point of the roster (#365) is that those two must not look alike. """ try: from ..celery_app import celery as celery_app if live is None: live = inspect_lanes_sync()[lane.name] if not live.present: return False, "lane is not running" control = celery_app.control for queue in lane.queues: if enabled: control.add_consumer(queue, destination=live.hostnames) else: control.cancel_consumer(queue, destination=live.hostnames) return True, None except Exception as exc: # noqa: BLE001 log.warning( "worker_control: could not %s %s", "enable" if enabled else "disable", lane.name, exc_info=True, ) return False, str(exc) # --- the settings half, which is async ---------------------------------------- # # Sync celery control above, async DB below, in one module. Same split # `service_roster` already runs (`_inspect_celery_sync` beside `touch_service`) # — the boundary is the transport, not the concern, and "control the workers" # is one concern. async def _rows_by_name(session: AsyncSession) -> dict[str, WorkerLane]: """Every lane's row, creating any that are missing from its LANES defaults. Self-heals rather than depending on a migration having run for a lane added later: alembic 0103 seeded the four that existed on 2026-09-22, and a fifth added to LANES afterwards gets its row the first time anything asks. Without this, a new lane would read as absent and the UI would simply not show it. """ rows = { row.name: row for row in (await session.execute(select(WorkerLane))).scalars() } missing = [lane for lane in LANES if lane.name not in rows] for lane in missing: row = WorkerLane( name=lane.name, slots=lane.default_slots, slots_cap=lane.default_slots_cap, enabled=lane.default_enabled, autoscale=lane.default_autoscale, ) session.add(row) rows[lane.name] = row if missing: await session.commit() return rows async def lane_view(session: AsyncSession) -> list[dict]: """Every lane: what is configured, what is live, what it may grow to. One call rather than making the UI join three sources. `pending` is the honest backlog — Redis depth PLUS reserved — because celery prefetches and LLEN alone reads 0 while a worker holds tasks in memory. """ rows = await _rows_by_name(session) live = await asyncio.to_thread(inspect_lanes_sync) depths = await asyncio.to_thread(_queue_depths_sync) oldest = await _oldest_running_by_queue(session) now = datetime.now(UTC) out = [] for lane in LANES: row = rows[lane.name] state = live[lane.name] # None for a queue the broker did not answer for, which must not be # silently summed as zero — an unknown depth is not an empty one. known = [depths.get(q) for q in lane.queues] depth = sum(d for d in known if d is not None) if any( d is not None for d in known ) else None out.append({ "name": lane.name, "display_name": lane.display_name, "queues": list(lane.queues), "slots": row.slots, "slots_cap": row.slots_cap, "ceiling": derived_ceiling(lane), "enabled": row.enabled, "autoscale": row.autoscale, "memory_bound": lane.memory_bound, "optional": lane.optional, # What enabling this lane will download, so the UI can say WHICH # model and how big BEFORE the switch is thrown rather than after # a multi-GB fetch has started. `measured` travels with the # numbers: the card must not present an estimate as a fact. "models": [ { "repo": m.repo, "download_bytes": m.approx_download_bytes, "resident_bytes": m.approx_resident_bytes, "measured": m.measured, } for m in lane.models ], "live": { "present": state.present, "replicas": state.replicas, "pool": state.pool, "active": state.active, "reserved": state.reserved, }, "queue_depth": depth, "pending": None if depth is None else depth + state.reserved, # How long the oldest still-running task on this lane has been # going, in minutes. The operator asked for a trigger here — grow # a lane whose tasks run past some duration — and it stayed a # REPORT: a long task does not finish sooner because the lane # gained a slot, so scaling on it would spend memory to change # nothing. Shown so they can see a lane wedged on one slow job, # which is the genuinely useful half of the idea. "oldest_running_minutes": _minutes_since( min( (oldest[q] for q in lane.queues if q in oldest), default=None, ), now, ), }) return out async def _oldest_running_by_queue(session: AsyncSession) -> dict[str, datetime]: """When the longest-running unfinished task on each queue started. Read from `task_run`, which is OUR OWN table on OUR OWN wall clock, and deliberately not from celery's `inspect active()`. Those entries carry a `time_start` taken from the WORKER's `time.monotonic()` — a clock with an arbitrary origin per process. Subtracting it from this process's wall clock produces a number that looks like a duration and is meaningless, and it would be meaningless in the direction that matters: plausible. `task_run` also already carries the per-queue staleness thresholds the recovery sweep uses, so a row still `running` here is one the system itself considers legitimately in flight rather than abandoned. """ result = await session.execute( select(TaskRun.queue, func.min(TaskRun.started_at)) .where(TaskRun.status == "running", TaskRun.finished_at.is_(None)) .group_by(TaskRun.queue) ) return {queue: started for queue, started in result if started is not None} def _minutes_since(started: datetime | None, now: datetime) -> int | None: """Whole minutes, or None when nothing is running. Never negative: a row written by a container whose clock is a few seconds ahead must read as 0 rather than as a task that starts in the future.""" if started is None: return None return max(0, int((now - started).total_seconds() // 60)) def _queue_depths_sync() -> dict[str, int | None]: """Redis LLEN per queue. None for one that did not answer — see lane_view. Sync; the caller threads it. A per-queue try/except so one bad queue does not cost the whole report, matching `api/system_activity._read_queues_sync`. """ import redis from ..config import get_config out: dict[str, int | None] = {} try: client = redis.Redis.from_url(get_config().celery_broker_url) except Exception: log.warning("worker_control: no broker for queue depths", exc_info=True) return {q: None for lane in LANES for q in lane.queues} for lane in LANES: for queue in lane.queues: try: out[queue] = int(client.llen(queue)) except Exception: # noqa: BLE001 — a hiccup must not break the UI out[queue] = None return out class LaneUpdateRefused(ValueError): """A requested value is outside what the lane may hold. Carries the reason the UI shows — a greyed control with no explanation reads as a bug.""" async def set_lane( session: AsyncSession, lane: Lane, *, slots: int | None = None, slots_cap: int | None = None, enabled: bool | None = None, autoscale: bool | None = None, ) -> dict: """Store the operator's choice, then push it to the running lane. BOTH, in one call, and the order matters. `pool_grow`/`pool_shrink` are not durable — a restart drops every lane back to its env concurrency — so a UI that only pushed would have its setting evaporate on the next deploy with nothing to show for it (lesson #4202: the live change does not survive, and nothing says so). Storing alone would be a number that describes nothing until something restarts. A failed PUSH is not a failed setting. The value is saved either way and step 3's reconcile carries it when the lane answers again; the result says `applied: false` with a reason so the UI can say "saved, not yet live" rather than "that didn't work". """ rows = await _rows_by_name(session) row = rows[lane.name] new_cap = row.slots_cap if slots_cap is None else slots_cap new_slots = row.slots if slots is None else slots new_enabled = row.enabled if enabled is None else enabled new_autoscale = row.autoscale if autoscale is None else autoscale ceiling = derived_ceiling(lane) if new_cap < 0 or new_slots < 0: raise LaneUpdateRefused("slots and cap cannot be negative") if new_cap > ceiling: raise LaneUpdateRefused( f"cap {new_cap} is above what this container can hold " f"({ceiling} for {lane.display_name})" ) if new_slots > new_cap: raise LaneUpdateRefused(f"slots {new_slots} is above the cap {new_cap}") row.slots_cap = new_cap row.slots = new_slots row.enabled = new_enabled row.autoscale = new_autoscale await session.commit() applied, error = True, None if enabled is not None: applied, error = await asyncio.to_thread( set_lane_enabled_sync, lane, new_enabled, ) if applied and slots is not None: applied, error = await asyncio.to_thread(set_lane_slots_sync, lane, new_slots) # Enabling a lane that needs models is what triggers the fetch (milestone # 422 step 6). Never at boot: that made every start of the ML role reach # HuggingFace for ~3.5GB, and rule 164 permits a runtime fetch only for a # feature that is optional and clearly OFF. # # Only when the lane actually came on — `enabled is True` rather than # `new_enabled`, so re-saving slots on an already-enabled lane does not # re-enqueue. And only when the consumer change landed: enqueueing a task # onto a queue nothing is consuming would leave it pending with no # explanation until the lane returns. fetching = False if enabled is True and lane.models and applied: fetching = _enqueue_model_fetch() return { "name": lane.name, "slots": row.slots, "slots_cap": row.slots_cap, "ceiling": ceiling, "enabled": row.enabled, "autoscale": row.autoscale, "applied": applied, "apply_error": error, # Tells the card to say a download has started rather than leaving the # operator to wonder why a freshly enabled lane is busy. "fetching_models": fetching, } def _enqueue_model_fetch() -> bool: """Queue the model download. Returns whether it was accepted. Import inside the function: `backend.app.tasks.ml` pulls in torch, and web must not pay that import cost on a module that every settings request touches. Never raises. A broker that will not take the task is worth reporting, but the SETTING has already been stored and the lane is already enabled — so failing the whole request here would roll back nothing and tell the operator their change did not happen when it did. """ try: from ..tasks.ml import ensure_models ensure_models.delay() return True except Exception: # noqa: BLE001 — reported, never raised at a caller log.warning("worker_control: could not enqueue the model fetch", exc_info=True) return False def reconcile_lanes_sync( desired: dict[str, tuple[int, bool]], autoscaling: frozenset[str] = frozenset(), ) -> dict: """Drive every RUNNING lane to its stored slots and enabled flag. `desired` is lane name -> (slots, enabled), read from the database by the caller. `autoscaling` names the lanes the autoscaler is allowed to move. ## For an autoscaling lane the stored value is a FLOOR, not a target Step 7's autoscaler raises a saturated lane's live pool without changing its row — the row holds what the OPERATOR set. If this pass treated that row as an exact target it would shrink the lane back on the very next tick, and the two sweeps would fight forever at five-minute intervals: grow, revert, grow, revert. That is lesson #4183's failure arriving between two enforcers rather than inside one. So for those lanes the target becomes `max(stored, current)` — this pass still restores a lane that came back from a restart below what the operator set, and never takes back what the autoscaler added. Bringing it down is the autoscaler's job, and it does so only to that same floor. This function touches no database: the celery task that schedules it owns the sync session, and keeping the DB out of here is what lets the same code be called from anywhere that already knows the target. ## Why this exists at all `pool_grow` is not durable. A worker that dies and is restarted by its supervisor comes back at its ENV concurrency — silently below whatever the operator set — and nothing in step 2's path would ever notice. Storing the value made it survivable; this is what makes it actually survive. ## It must converge and then go quiet One `inspect` for all lanes, and `set_lane_slots_sync` issues nothing at all to a replica already at its target. So a settled system performs one broker round trip per tick and sends no control messages — the reachable fixed point lesson #4183 is about. An enforcer that re-sent a grow of zero every tick would churn forever and bury a real correction in its own noise, which is why `changed` below counts only lanes that actually moved. ## An absent lane is SKIPPED, not corrected `present=False` means nothing answered — a worker restarting, or a broker that is unreachable. It does NOT mean zero slots. Correcting an absence would be drawing a conclusion from an unswept read (snippet #3969), and here it would be worse than useless: there is nothing to send the message to. The lane is reported as skipped and picked up on a later tick. """ live = inspect_lanes_sync() changed: list[str] = [] skipped: list[str] = [] failed: dict[str, str] = {} for lane in LANES: target = desired.get(lane.name) if target is None: continue slots, enabled = target state = live[lane.name] if not state.present: skipped.append(lane.name) continue # Enabled first: a lane being turned on should be consuming before # its pool is sized, so the slots it gains have work to pick up. # # Only when it DISAGREES. Calling this unconditionally would send # add_consumer for every queue on every tick of a settled system — # the exact churn lesson #4183 describes, and invisible because # add_consumer on a queue already consumed is harmless. consuming_all = state.consuming.issuperset(lane.queues) if enabled != consuming_all: ok, err = set_lane_enabled_sync(lane, enabled, live=state) if not ok: failed[lane.name] = err or "could not set consumers" continue changed.append(lane.name) current = state.pool # The floor, for a lane the autoscaler manages. See the docstring. target_slots = slots if lane.name in autoscaling and current is not None: target_slots = max(slots, current) if current is not None and current == target_slots: continue ok, err = set_lane_slots_sync(lane, target_slots, live=state) if ok: if lane.name not in changed: changed.append(lane.name) log.info( "worker_control: %s reconciled %s -> %s slots", lane.name, current, target_slots, ) else: failed[lane.name] = err or "could not resize" return {"changed": changed, "skipped": skipped, "failed": failed} # --- the autoscaler (step 7) -------------------------------------------------- # # The only part of this milestone that acts without anyone asking. Everything # above does what an operator pressed; this decides. So it is off by default, # opted into per lane, bounded by the cap the operator set, and it reports what # it did rather than moving numbers silently. # ## Why these three numbers are not in Settings # # Rule 25 puts anything an operator might want to tune in the UI, and the # knobs that decide what this does ARE there: whether a lane autoscales at # all, its cap, and its floor — all DB-backed, all changeable without a # restart. What is left here is the POLICY's internals, and exposing them # would add four numbers per lane to a card whose whole value is being # readable at a glance, to tune a decision the operator has a better lever # for. If growth turns out to be too eager or too shy in practice, that is a # reason to change these values for everyone, not to ask each operator to # discover them. # All slots busy AND this many tasks waiting before a lane may grow. # # The AND is the design. Depth with free slots means nothing — celery is about # to pick those up, and growing the pool would add idle children. Saturation # with an empty queue means nothing either: the lane is busy with exactly as # much work as exists. Only both together say "there is more work than this # lane can reach". AUTOSCALE_BACKLOG_THRESHOLD = 10 # Grow by one slot per tick, never to the cap in one jump. A lane that is # saturated because of one slow burst settles a slot or two above where it # started rather than at its ceiling, and the next tick re-measures rather # than committing to a guess made once. AUTOSCALE_STEP = 1 # Hysteresis: shrink only when the backlog is well BELOW the grow threshold, # not merely under it. Equal thresholds flap — one task arriving and leaving # would grow and shrink the lane forever at the tick interval, which is # lesson #4183's churn arriving through a different door. AUTOSCALE_SHRINK_BELOW = 2 @dataclass class AutoscaleDecision: """What the autoscaler did to one lane, and why — in the operator's terms. A reason string on every outcome including "nothing", because an autoscaler that only speaks when it acts is one nobody can debug when it does not. """ lane: str action: str # "grew" | "shrank" | "held" slots: int reason: str def autoscale_lanes_sync( lanes: dict[str, tuple[int, int, bool]], ) -> list[AutoscaleDecision]: """Decide and apply one round of autoscaling. `lanes` is name -> (slots_cap, configured_slots, autoscale_on), read from the database by the caller — this function touches no database, for the same reason `reconcile_lanes_sync` does not. ## What is current, and what is the floor The value this moves is the LIVE pool, read from `inspect`. The stored `configured_slots` is what the operator set and is only the FLOOR: growth goes above it and a shrink returns to it, never below. The two are deliberately not the same number, and reading the stored value as "current" is the mistake that makes this function useless in a way no unit test of a single tick would show. The autoscaler never writes the row, so the stored value never moves; a tick that computed `stored + 1` would propose the same target forever, cap the lane one slot above the floor no matter the load, and — because resizing a replica already at the target issues nothing and reports success — claim `grew` on every tick while nothing changed. Lesson #4183's non-convergence, arriving with a success message attached. So: `current = state.pool`, `configured` is the floor, and both `grew` and `shrank` mean the live pool actually moved. """ live = inspect_lanes_sync() depths = _queue_depths_sync() out: list[AutoscaleDecision] = [] for lane in LANES: target = lanes.get(lane.name) if target is None: continue cap, configured, on = target if not on: continue state = live[lane.name] if not state.present or state.pool is None: # Nothing answered. Not "idle" — unknown, and a decision drawn # from an unswept read is exactly what snippet #3969 warns about. # `configured` is reported because there is no live number to # report; it is what the lane will come back at. out.append(AutoscaleDecision( lane.name, "held", configured, "lane is not answering", )) continue current = state.pool known = [depths.get(q) for q in lane.queues] if all(d is None for d in known): out.append(AutoscaleDecision( lane.name, "held", current, "queue depth unavailable", )) continue backlog = sum(d for d in known if d is not None) + state.reserved # Against CAPACITY, not against the dial: `active` is summed across # replicas, so comparing it to one replica's pool size would call two # half-busy replicas of 4 saturated at 4 active and grow a lane that # has idle slots. saturated = state.active >= state.capacity > 0 busy = backlog >= AUTOSCALE_BACKLOG_THRESHOLD if saturated and busy and current < cap: new = min(cap, current + AUTOSCALE_STEP) ok, err = set_lane_slots_sync(lane, new, live=state) out.append(AutoscaleDecision( lane.name, "grew" if ok else "held", new if ok else current, f"{backlog} waiting and all {state.capacity} slots busy" if ok else f"could not grow: {err}", )) elif saturated and busy: # At the cap with work still waiting. Said out loud rather than # held silently: this is the operator's own ceiling doing its job, # and it is the moment they would want to know they set it. out.append(AutoscaleDecision( lane.name, "held", current, f"{backlog} waiting but the cap is {cap}", )) elif current > configured and backlog <= AUTOSCALE_SHRINK_BELOW: new = max(configured, current - AUTOSCALE_STEP) ok, err = set_lane_slots_sync(lane, new, live=state) out.append(AutoscaleDecision( lane.name, "shrank" if ok else "held", new if ok else current, f"backlog cleared, back toward {configured}" if ok else f"could not shrink: {err}", )) else: # The fixed point. A settled lane sends nothing and says so — # the tick is one inspect and one LLEN sweep, no control messages. out.append(AutoscaleDecision( lane.name, "held", current, f"{backlog} waiting, {state.active} busy", )) return out